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An economic efficiency study on different regions of Ghana via Slack-based data envelopment analysis and regression analysis

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  • Orla A. Murphy
  • Ping Wang
  • Sunny X. Wang
  • Greg Tkacz

Abstract

In this article, we evaluate the efficiency of the 10 different regions of Ghana using slack-based data envelopment analysis, a nonparametric linear programming technique. Furthermore, we analyse the variable effects on the efficiency of the regions by various regression models using bootstrap sampling technique. The data come from the 1991/1992 and 1998/1999 Ghana Living Standards Survey. Our results show that wealth is not strongly related to efficiency. For example, the study indicates that the Brong--Ahafo region is the most efficient region but not the most wealthy in Ghana. Generally, urban regions are not found to be among the most efficient regions due to the high expenditures. The regression analysis shows that female heads of household have an overall positive effect on efficiency. In addition, any form of education obtained is also found to have a significant positive effect on efficiency.

Suggested Citation

  • Orla A. Murphy & Ping Wang & Sunny X. Wang & Greg Tkacz, 2013. "An economic efficiency study on different regions of Ghana via Slack-based data envelopment analysis and regression analysis," Applied Economics, Taylor & Francis Journals, vol. 45(34), pages 4773-4780, December.
    • Handle: RePEc:taf:applec:v:45:y:2013:i:34:p:4773-4780
    DOI: 10.1080/00036846.2013.804170
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    1. Mei Xue & Patrick T. Harker, 1999. "Overcoming the Inherent Dependency of DEA Efficiency Scores: A Bootstrap Approach," Center for Financial Institutions Working Papers 99-17, Wharton School Center for Financial Institutions, University of Pennsylvania.
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    Cited by:

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    2. Oliviero A. Carboni & Paolo Russu, 2018. "Measuring and forecasting regional environmental and economic efficiency in Italy," Applied Economics, Taylor & Francis Journals, vol. 50(4), pages 335-353, January.

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